WN11 and FB13) sampled from WordNet and Freebase.

distance Model (Bordes et al., 2011), Hadamard Model , Single Layer Model (Socher et al., 2013), Bilinear Model (Sutskever et al., 2009;Jenatton et al., 2012) and Neural Tensor Network (NTN) 15 (Socher et al., 2013)), our model TransM still achieves better performance as shown in Table 8.


Bordes et al (2013b;2013a) conduct experiments on each subset respectively.

bordes et al (2013b;2013a) conduct experiments on each subset respectively.


The size of WN18 dataset is smaller than FB15K, with much fewer relationships but more entities.

the result shows that TransE can only achieve less than 20% accuracy 6 when predicting the entities on the MANY-side, even though it can process ONE-TO-ONE triplets well.


In the manual manner, we manually select the Web pages that describe the labels.

the procedure for learning the DBN with three RBMs is shown in Figure 4.


Now the identifier corresponding to w1H will be H_PRP as मैं is a Hindi personal pronoun.

some examples from this dataset are given below.


• In addition to n-grams of characters, we use frequency of usage of a word in English and in Hindi languages as features for word-level language identification.

∀ word q ∈ Hindi Dictionary For a given word w in the test data, score(w) = log( freq(hw))/M hin_score(hw) = score(w) … we get English score and Hindi score for each word in the Dataset 1.


We use candidate analogies to rank the two candidate antecedents for the target pronoun in a given source sentence.

in the case of multiple dependents, we only select the rightmost one.


Our approach is a pure example-based strategy, which requires no training data.

(2012) examined the use of page counts and found the stability issue.


In the source sen-tence (17), the subject of the adjective clumsy is more likely to be an animate noun (e.g., cat) than an inanimate noun (e.g., glass).

for a computer program, this pronoun resolution becomes extremely difficult, requiring the use of world knowledge and the ability to reason.


The current study cannot provide any elaborate answer to this, but would note that recent studies have found commonalities across categories in English, such as the measurement of predicates in various constructions (Wellwood, Hacquard, & Pancheva, 2012;Champollion, 2010;Krifka, 1998).

in a broader sense, the current analysis shows the benefit of a simpler syntax-semantics mapping mechanism in language.


structure 14shows that gwo3 must not be a head.


For instance, that's true has never been found to answer a previous question in the corpus, while 3% of that's right can perform this function.

it is noted that the top three functions of that's right are exactly those functions analyzed and discussed in the literature, that is, agreement, assessments and affirmative answers.


that's right, that's true, that's correct) and their variations in the Switchboard Dialogue Act Corpus.

in order to see whether their previous contexts could offer useful cues to differentiate the occurrence of that's right and that's true, a specific view is taken into the previous contexts when they act as accept and assessment/appreciation, because the two functions together make up a large proportion of the total occurrence.


They were prohibited to use dictionaries or any other reference books.

we propose an automatic method that statistically measures listenability for EFL learners.


Learner features must show the listening proficiency.

learners have different proficiencies; thus, individual differences of listening proficiency should be considered.


In most of the sentences collected here, there are pitch peaks in the beginning of an utterance, but the last two or three syllables show a gradual decline until the boundary tone.

i am grateful for the financial support of this project provided by the Bilinski Educational Foundation, the University of Hawai'i Arts and Sciences Advisory Council and the Department of Linguistics Endowment Fund.


Sarcasm is known as "the activity of saying or writing the opposite of what you mean, or of speaking in a way intended to make someone else feel stupid or show them that you are angry" (Macmillan, 2007).

if one pair of w 1 and w 2 satisfies our rules among all combination of w 1 and w 2 in multiple sentences in a tweet, we regard the overall tweet as coherent.


A variety of methods have been proposed based on various kinds of techniques, including statistical models, sentiment analysis, pattern recognition, supervised or unsupervised machine learning.

it can be classified as a sarcastic sentence.


As we will describe in 4.4.2, the total scores will also be used as weights in the feature vector in the classification process.

some expanded concepts may be irrelevant with the context of the tweet.


Reddy and Knight (2011) developed a languageindependent model based on a Markov process that finds the rhyme schemes in poetry and the model stanza dependency within a poem.

the candidate scoring the highest PACLIC 28 !


In this study, a fluent, easily sung lyric has been generated from the previous word w l−1 , the mora length m l of the word, and the hidden state C verse i or C line i,j .

(2009) generated melodic lyrics in a phonetic language (in their case, Tamil).


The dataset contains 24,000 songs, 136,703 verses/choruses, 411,583 lines, and 61,118 words.

we have (b), (c) The second and third proposed models is implemented for generating a consistent lyric.


Therefore, given-new ordering is expected to mitigate the processing cost of STOPOV, OACCSV, and OTOPSV.

planned comparison revealed the effect of the morphological factor to be significant in OSV (F1(1, 126) = 12.29, p < .001; F2(1, 22) = 11.58, p < .005) but not in SOV (F1(1, 126) = 0.47, n.s.


money-ACC give-IMP-QT say-PAST 'The robber, pointing a pistol at me, said, "give me money". '

even in given-new condition, the processing cost of the scrambled word order was higher than that of the canonical counterpart.


(9) Hypothesis based on Markedness Principle for Discourse-Rule Violations: SNOMOACCV and STOPOACCV are not penalized when they violate given-new ordering because they are unmarked options.

there are choices between topic marker and case marker: SNOM vs STOP and OACC vs. OTOP.


Some scholars treat yone as a sequence of the two discourse particles yo and ne.


He was talking fast about something with a young man who looked like an assistant, but stopped the conversation when he caught sight of me.

(relevant examples: (9)-(14)) c. In an utterance that does not meet none of the conditions described above, yone must be chosen, or at least is strongly preferred.


), verbs (odůvodnit 'to give reasons', vysvětlit 'to explain', znamenat 'to mean' etc.)

in the data, the individual connective key words (like reason, due to, because of, condition etc.)


We may see that relations of secondary connectives form 5 % of the total number.

from this reason, they were expelled from the Czech Republic these days.'


It is also shown in Table 3 how discourse relations in our method correspond to those in K&B and those in SDRT.

we applied our method to 128 sentences from BCCwJ (Maekawa, 2008).


The temporal requirement Precedence(π2,π4) is that realization of a pain precedes the inference of the strain, which is also as expected.

usages such as that illustrated in (2) and interactions between temporal relations and causal relations were not analyzed.


(2005) characterized causal expressions in Japanese text and built a Japanese corpus with tagged causal relations.

we have to show how our simplified setting is still free from that contradiction.


Finally, we conclude this study in section 5.

here, ROUGE-1 and ROUGE-2 are metrics based on unigram and bigram matching between the referential summary and a generated summary, respectively.


Although many useful smoothing techniques are developed to estimate these unseen sequences, it is still important to make full use of contextual information in training data.

a number of useful smoothing techniques such as back-off (Katz,1987), Kneser-Ney (Kneser & Ney,1995), modified Kneser-Ney (Chen & Goodman,1999) have been developed to estimate the probabilities of unseen sequences.


These can be separated into classes PACLIC 28 !

here a c denotes the addressee of the current context.


This language has a number of means for indicating politeness.

the particles can combine with other terms with honorific content, and need not match them perfectly in register, as will be shown in the next section.


wa-marked declaratives can be rendered into interrogatives without any problem as in (11).


⟨w3, w3⟩ ⟨w4, w4⟩ s1: If these extra world pairs are added to both blocks of the partition specified in the derived context, then the resulting relation does not obey mutual exclusivity, as illustrated in (37).

the difference is the speaker's intention in the discourse.


In the current case, however, the act is a question (i.e., an inquisitive update), creating a partition over those multiple contexts, as depicted in (48).

in (15), the speaker is indicating that she is willing to make assertions only about John and the alternative speech acts about other individuals are cancelled.


We observed the attributes in the conversation and calculated the appearance probability of the attributes.

we cannot divide the chunk of utterances as independent conversations.


Second, the system confirms whether the terminal expression of the verb will degrade the translation quality.

the input utterance "もっと買わなきゃだ (It is necessary to buy it more)" is processed by the four steps and then the untranslatable colloquial expression "買わなきゃだ" is detected.


The acceptability did not change in 1,163 (52.2%) utterances, and the acceptability decreased in 60 (2.7%) utterances.

our research proposed a procedure for detecting the untranslatable colloquial expressions automatically.


Not every sentence marked with these categories is a comma splice since the error tags cover other error types as well, e.g., fused sentences, missing conjunctions for NPs, missing complementizer "that", etc.

we did not include comma splices introduced by fusing sentences together.


Thing of result only if do finish complete then know "The result can only be known after you have finished doing it."

and this is exactly the function of post-preterite tense in English.


In (9a) the focus is on the fact that the sixth bottle is empty, while in (10a) the focus is on the burst of the balloon.

he claims that tense is a concept related to both speech event and narrated event.


Since "verb+guo2" represents an event as a whole rather than a process of realization, "x" and "a" coincide in the diagram.

"guo1" is the unmarked category, giving no specific information about the time when the verbal action takes place, while "guo2" is the marked category signifying the sense of "happened in the past".


(2) A language L favors N1 attachment if: a. L has no alternative construction for expressing the N1 interpretation (Frazier and Clifton, 1996); b. L has flexible word order (Gibson et al., 1996); c. L allows constituents (e.g., adverbs) to intervene between a verb and its direct object (Miyamoto, 1999); d. L exhibits consistent use of relative pronouns (Hemforth et al., 2000); e. L has pseudo-RCs (Grillo, 2012); f. L allows constituents (e.g., adjectives) to intervene between the modified noun and the RC (schematically: N adjective RC, the modifier-straddling hypothesis, MSH, Cuetos and Mitchell, 1988).

the most lenient languages such as Romance languages have both triggers.


Wald chi-square was used to calculate p-values (function Anova in the package car; Fox and Weisberg, 2011).

in order to measure the influence of the context surrounding the complex NP, tokens were classified according to whether information inside the complex NP was enough to determine attachment (internally disambiguated; e.g., voice of men that was uttered) or whether it was also necessary to consult the context surrounding the complex NP (externally disambiguated).


Segments with thî: preceded by khɔ̌:ŋ "of" within a three-word window were extracted from the six writing genres of the Thai National Corpus (Aroonmanakun et al., 2009), namely fiction (which contains 7,469,530 words), newspaper (5,029,019 words), academic text (8,894,650 words), nonacademic text (5,342,092 words), law (1,190,516 words) and miscellanea (4,000,160 words).

the corpus count suggests that surrounding context can play a role in RC attachment and the bias is often but not exclusively to N1.


the "world" set), then the meaning of "students" is regarded as a set student ✓ W containing all entities being students, and the meaning of "(someone) likes noodles" is regarded as a subset of W which contains all entities who like noodles.

instead of numbers in the original DCS tree to denote different dimensions (i.e.


Or even if he does the shop assistant does not detect his expectation about the vase.

this paper addresses the influences of common ground, context and information structure on the linguistic production and interpretation processes with a special reference to counter-expectation in thai.


This means that: 1) B had a prior expectation, ✏ M ( 3 ) ✏ + M p; 2) A's first assertion indicates that p is no longer supported by the expectation state, This contradicts the secondary component of the semantics of A-NOT-A question,  Table 4, among the four Cantonese polar questions considered in this paper, only AA4 questions are simplex questions while HO2, ME1 and A-NOT-A questions have multidimensional semantics.

this paper thus offers a solution to this problem in the framework of inquisitive semantics (Groenendijk & Roelofsen, 2009), where meaning of sentences are given based on support-conditions.


Yuan & Hara (2013) argue that the assertion of 'p or not p' in effect indicates the ignorance of the speaker, hence the neutrality requirement.

yuan & Hara (2013) argue that the assertion of 'p or not p' in effect indicates the ignorance of the speaker, hence the neutrality requirement.


In addition, they seem to impose different restrictions of animacy on the object B.

given this, the agentive fan is to a certain extent similar to the verb start in English.


That is, the [-m] role, as an under-specified role, cannot bear the ACC feature.

the disparity mainly lies in the mental use of fan "be annoyed", which is not only unattested in the corpus of taiwan Mandarin but also reported as weird by our informants.


It should be further noted that the above mentioned inanimate entities can never function as the subject of the causative fan "annoy".

the latter use of fan, as that in (6), is unattested in Taiwan Mandarin.


Metonymy, on the other hand, refers to a process which uses a salient entity that is easy to understand as the referent point that links to a less salient entity (Langaker, 1999).

lakoff and Johnson (1980) state that conceptual metaphor is a language phenomenon in which a speaker understands a particular concept through the use of another concept.


it shows the words that have a statistically significant association with the keyword.

section 2 provides some background about corpus-based discourse analysis and discusses some limitations of the automated techniques that are commonly used.


Then, the context similarity for each extracted noun and the noun in the input sentence is  In this method, we hypothetically define the prephrase and post-phrase of the target noun as the context; nouns used in a similar context are extracted from the corpus.

they regard English word 5-gram as one phrase, and they generate feature vectors using pointwise mutual information (PMI) scores.


However, in this study, we evaluate the performance of our generation method independently from the quality of automatic word or phrase alignment algorithms.

in our study, the class for SVM is each phrase in a paraphrase set, which contains a source phrase.


This approach constructs k(k-1)/2 classifiers, where k is the number of classes, with a training data set from two classes.

these methods tend to encounter two problems when applied to agglutinative languages (e.g., Korean, Japanese, and Turkish), which are morphologically rich languages.


One may think that it is sufficient to simply enumerate frequent-enough words or N -grams and use them as a whitelist to avoid suppressing their occurrences.

lCP i is defined as the length of the maximum common prefix of two lexicographically neighboring suffixes T SA i 1 ..n and T SA i ..n , where T is the string in concern and SA is the suffix array of T .


558913) and the Newly Recruited Junior Academic Staff funding of the Hong Kong Polytechnic University (Grant Account A-PL27).

finally, we will briefly discuss the contribution and future directions of this line of research.


We restrict to Pattern 1 in reconstructing of source bigrams because this Pattern contains more information of context and crossing-language alignment.

then we translate unseen bigrams based on proportional analogy and filter the outputs using an Support Vector Machine (SVM) classifier.


Challenging not only because speech recognition and speech synthesis are involved, but also because of the lack of dialectal Arabic parallel corpora.

at the best of our knowledge, PaDIC, up to now, is the largest corpus in the community working on dialects and especially those concerning Maghreb.


The experiments for the random baseline were performed 1,000 times.

we eventually used the following transition probability parameter to avoid the zero frequency problem: where α a denotes a transition probability parameter where all the leaf nodes have the same amount probability and α s b denotes the transition probability parameter that is pre-trained using the above equations.


If so, all the probabilities of all the paths from the root node to each leaf node would have been the same.

in addition, we deleted word senses that appeared only once through pre-processing.


Neg_Sentiment_Fea is feature measures shallow sentiment of sentences, we manually chose a list NEG_SENTIMENT = {'no ', 'not', 'never', 'little', 'few', 'nobody', 'neither', 'seldom' 'hardly', 'rarely', 'scarcely'} to judge the sentiment, the appearance of word in this list indicating an opposed meaning, if only one word in the list appeared only once in this pair of sentences, we think that this pair of sentences expressing opposite meaning.

in our experiments, we also used plenty of style-related features, we call it "literal-based" features.


In terms of implementation, we used Scikit-learn 5 toolkit (Pedregosa, Varoquaux et al., 2011) to do the classification and the parameter settings for three SVR models are shown in the following table, we chose these parameters by experiences, Clf-2 and Clf-3 used the same setting, and a better result may be achieved through fine tuning: 'rbf' 0.16 100 0.1 Table 3 Parameter settings of our three classifiers After the prediction of the similarity scores of sentences, we conducted a post-processing step to boost and correct results, we truncate at the extre-    Table 4 reported the results of our method on SemEval 2015 Task 2a, from which we can know that our method outperformed the winning system by a big margin on the headlines, but only slightly better on the images.

we can get vector representations 1 and 2 of the two sentences.


Secondly, what's more difficult is to recruit highly diverse subjects due to the difficulties in subject recruitment and the spacial limitations of laboratory-based experiments.

we also investigated the uncertainty of semantic transparency judgment among raters, we found that it had a regular relation with semantic transparency magnitude and this may further reveal a general cognitive mechanism of human judgment.


Since in our compound stimuli, there are completely transparent compounds and completely opaque compounds, so ideally, two kinds of results should share and cover the same scale from 0 to 1.

the adjusted normalization method has an advantage over the standardization method, that is the adjusted normalization will yield results from 0 to 1 and this scale is accord with the definition of semantic transparency value.


Input sentences are split into words by a morphological analyzer MeCab 1 (we used this analyzer throughout the paper).

the upper two examples show utterance pairs that were classified correctly by all methods, while the two examples at the bottom were correctly classified by only the (RNN + DP + diff) method.


As shown in the above, position feature (PF) contains two elements, and relative-dependency feature (Relative-Dep) contains three elements.

the main challenge is the fact that important information can appear at any position in the sentence.


Furthermore, we analyze the performance influenced by other different features, and finally the F1-measure is improved to 0.545.

there are inadequate free texts locally for extracting features, as Freebase is a well-structured knowledge repository with billions of triples.


We compute principal component scores for r dimensions by applying SVD to B.

the computation time of APPROX-PMI+PCA was much smaller than that of EXACT-PMI and APPROX-PMI.


We form noun phrases whose scores are greater than a threshold.

the similarity computation between patterns is crucial for unsupervised relation extraction.


The plots show that, for similar words, the learned weights for the corresponding lexical features are only slightly similar; but after the lexical features are reduced to low-dimensional embedding features, the learned weights for the corresponding features are more strongly correlated.

the plots show that, for similar words, the learned weights for the corresponding lexical features are only slightly similar; but after the lexical features are reduced to low-dimensional embedding features, the learned weights for the corresponding features are more strongly correlated.


By appropriate representation learning (usually by back-propagations in neural network), these embeddings can replace traditional sparse features and perform quite well together with neural network.

it is not the case for our neural network as the output layer of our network only has two neurons.


Next, we explore the possibility of using a recurrent neural network (RNN) to induce multilingual NLP tools, without using word alignment information.

the combined model is built for each considered language using cross-validation on the test corpus.


In Figure 2, the input vector is obtained from Equation 2 and dA1 is applied with the weight matrix of the first layer W 1 to calculate the first hidden layer.

as can be seen from Table 1, the number of nodes has little or no effect on accuracy, whereas changing the number of layers helps to improve the performance.


1-of-K treats different words as discrete symbols.

using an SdA, the result for Bagof-Features was 76.9% and that of distributed word representation was 81.7%.


We can speculate that Polish people feel involved in this war, as a Polish engineer was kidnapped and killed by Pakistani extremists.

this may be caused by the following reasons: first, Bosnian Wikipedia is not as widely used as some other languages (ranked 69 in number of Wikipedia articles 11 ), which will result in a limited number of edits on these articles; second, the Civil war in tajikistan has little relevance to the people speaking, e.g., Italian or Portuguese, because of the geographical distance, which may result in limited attention to this topic.


They show that surface patterns are much more accurate (from 45% to 85%) than deeper linguistic information.

a window size of five is used to verify whether negations are present.


they are incoherent), conflict of the polarity may not indicate the sarcasm or irony.

formally, the polarity feature can be represented as a (key, val) pair, where the key is <pos, dict>, or <dict>.


In addition, Sutheebanjard and Premchaiswadi (2010); Lertcheve and Aroonmanakun (2009) mentioned a similar extracting pattern.

the MA set has only the positive and negative sense and does not have the neutral sense of 'stock price'.


The training set contains no neutral sentiment.


In Arabic language, sentiment resources are in general rare.

with the expanding growth of social networks services, user generated content web has emerged from being a simple web space for people to express their opinions and to share their knowledge, to a high value information source for business companies to discover consumer feedbacks about their products or even to decide future marketing actions.


This analysis can unify the blocking effect observed not only in Chinese but also in Japanese and Korean, and more clearly accounts for why there is a blocking effect in these languages.

it has been observed in the literature (Clements 1975, Sells 1987, Kuno 1987, Stirling 1993, Pearson 2013, among others) that a logophoric pronoun commonly manifests the three properties listed in (1).


That is, the camera is placed at equal distance from both John and Mary.

log-receive gift 'Amai heard from Kofij that shei/hej had received a gift.'


It can always have the source as its antecedent.

to (33), on the other hand, the sentence in (34) does not occur in the logophoric environment.


The following sentence is compatible with this idea.

it is worth noting that there is no attitude predicate in (27).


10 There are at least two possible ways for (10) to be derived under the analysis in question.

an alternative analysis would reattach the cops to the matrix TP or CP, where the cops could ccommand they.


This extraction, however, violates the Sentential Subject Constraint, resulting in the RRC effect.

at this point, the strategy may be successfully applied: The parser integrates John as a subject, postulating a trace in the specifier position of the vP such that the trace can be assigned a theta-role by the verb saw, the theta-role being transmitted through a chain to the subject John.


Here, however, the final attachment site in the jar (=β) does not c-command the original attachment site into my mouth (=α); this results in a high-cost reanalysis.

hence, the dislocated NP is properly licensed.


RVC pattern is therefore not used in Cantonese corresponding sentences.

rVC-patterns in causatives are strictly prohibited.


The idea is that the P-type MSC in (4b) is derived by PR from a single subject construction (SSC) where the first NP is licensed as a Possessor (cf.

these MSCs must be licensed differently.


Spaces are used for easier reading and generally put between phrases, but there are no clear rules for using spaces in Khmer language.

first, we trained a CRf model from 5,000 manually segmented Khmer sentences.


The operation types are (i) generation of a sequence of source and/or target words (ii) insertion of gaps as explicit target positions for reordering operations, and (iii) forward and backward jump operations which perform the actual reordering.

in all-but-one of the evaluations involving Japanese and Korean the HPB-SMT approach gave rise to the highest scores.


Word segmentation is helpful in Chinese natural language processing in many aspects.

because CSLM outperforms bNLM in probability estimation accuracy and bNLM outperforms C-SLM in computational time.


Traditionally, Back-off N-gram Language Models (BNLM) (Chen and Goodman, 1996;Chen and Goodman, 1998;Stolcke, 2002) are being widely used for probability estimation.

most of the other factors are fixed when we discuss one single factor.


Since these two approaches still adopt head-dependent structure as the backbone of the translation rule, the freedom of generating translation candidates is limited.

in the future, we will explore more powerful features to better score the translation candidates.


Both of them report improvement of about 0.9 point in BLEU score over the baseline on their dataset.

there are two typical problems for this approach.


Conversion is done by (i) collecting conversion candidates from various utterances on the Web (e.g., Twitter postings), which are annotated with their authors' personal attributes (this paper deals especially with gender, age, and area of residence), and (ii) using syntactic and semantic filters to suppress the generation of ill-formed utterances.

we conducted two experiments to investigate the performance of our proposed method of converting sentence-end expressions.


Table 6 lists the examples of the surviving candidates that are characteristic of the female attribute.

these utterances all convey the meaning that corresponds to 'Do you want to go to school?'


We conducted two experiments to investigate the performance of our proposed method of converting sentence-end expressions.

the annotation of the authors' personal attributes to the postings was done based on the self-declarations by the authors.


Eventually, some interesting findings are obtained.

in the following study, we will expand the research scope and test more interactions between synaesthesia and the cognitive modelling, through which we hope that our studies could contribute to bridging the research on synaesthesia in linguistics and that in neuroscience eventually.


Both 聲 and 音 are in the auditory domain, which can denote the sound, thus, both of them can inherit common semantic information from the upper concept, namely sound.

similarly, Hong and Huang (2004), Hong and Huang (2005) also pointed that semantic/cognitive features embedded in perceptual near synonyms can influence their usages in the language.


聲 is much easier to be described through synaesthesia than 音, and also employs higher symmetry on synaesthetic selection of modifiers.

聲 seems to be much easier and more common to be described than 音 through synaesthesia.


This paper is devoted to a fine-grained study on the interaction between synaesthesia and the near synonyms 聲 and 音 of the auditory domain in Mandarin Chinese.

聲 and 音, as a pair of near synonyms in the auditory domain, have both similar properties and different characteristics on synaesthesia.


In the third and fourth procedures, the chat logs are exported by the corpus developers in charge of proofreading the annotations.

for the rest of the criteria, the workers answered using 6-point Likert scale: 6 for excellent, 5 for good, 4 for rather good, 3 for rather poor, 2 for poor, and 1 for terrible.


In addition, there are three hypotheses about the production process of speech and gesture: the Free Imagery Hypothesis (Krauss et al., 1996(Krauss et al., , 2000de Ruiter, 2000), the Lexical Semantic Hypothesis (Schegloff, 1984;Butterworth & Hadar, 1989), and the Interface Hypothesis (Kita & Ö yzürek, 2003).

this hypothesis predicts that gestures do not convey the information which is not encoded in the accompanying speech.


In addition, Chinese consists of a large number of homophones, which allows a syllable to correspond to many different characters with various meanings.

within a neuronal embodiment account (e.g., Pulvermueller, 2013), we could argue that it is due to differences in the neural encoding of the two modes of training.


the validity of this method, which makes the evaluation of sentence-bysentence comprehension possible, has been acknowledged (Ross 1998).


These properties have been used to statistically classify learners' output into a range of proficiency levels (Thewissen 2013).

their learner corpus was composed of data from 30 native English speakers and 90 EFL learners classified into three levels according to tOEIC scores.


Their learner corpus was composed of data from 32 EFL learners classified into three levels according to Test of English for International Communication (TOEIC) scores.

the present study proposes to annotate listening comprehension data for individual sentences, which is expected to offer a finergrained analysis for the identification of learners' linguistic problem areas.


This study proposes a rule-based, signal-processing agent-based model to reveal the dynamics of language development in early infants.

as the examples shown in Table 1, infants are gradually aware of what they hear, where the sounds come from (sound localization) and what are the differences between them (consonant and vowel distinctions).


So, the Rule R1: if the SA is composed of more than one token and a common SC is shared between tokens, then the relevant SC is the shared one.

the third SB characterizes the intransitive syntactic construction "SV" ((S) followed by a (V)).


脈 mai "meridian": "The blood vessels, distributed all over the human body and animal body, carry blood everywhere."

we choose to analyze the four atypical body parts: 血, 肉, 骨, 脈, each of which is defined by the online dictionary compiled by the Ministry of Education, Taiwan (MOE Dictionary) as 1 血 xie "blood": "The red fluid in the veins/vessels of higher organisms, which starts from the heart and circulates throughout the body.


(14) has the extra than phrase 'than the page limit' within the izyooniclause.

3 Note that the proposition is now type <s,t> due to the situation semantics.


Their primary goal is to account for the positive implication of izyooni-comparatives.

at the same time, it suffers from the same problem that Shimoyama (2012) does, namely, overgeneration.


in doing so, we need to come up with non-event semantics, because many izyooni-comparatives, including (1) and (13), are not eventive.


To my knowledge, there are three previous studies of izyooni-comparatives.

35 other analyses are somewhat compatible with the lack of positive implication in (35).


On the first set of all DDs, three out of four slopes of the line-of-best-fit have positive slopes, but the slope for Adjunct island type has a negative slope.

the prosecutor"s dish was lost because it was not based on fact.?


Crucially, there are no significant interaction effects of GAP-POSITION and STRUCTURE for the Adjunct and Subject island types.

we performed the two pairwise comparisons on the embedded GAP-POSITION condition and the non-island STRUCTURE condition to test for each independent effect of STRUCTURE and GAP-POSITION.


Some other nominal categories, such as entity nouns and dongzuo-marked nouns, allow individualization in two different dimensions.

dongzuo-marked nominal is an event noun while xingwei-marked nominal tends to be an entity noun.


(SC) any raise_the_investment DE action 'It is not recommendable for investors to increase their investment in any forms.'

such a difference may not be applicable to all the entity nouns.


This is one of examples showing the property-sharing constraint.

since the topic is the highest position of the forward looking center ranking, the last candidate is likely to be the antecedent of the zero object.


The accuracy of the proposed method reached 73.37%.

the object of the sentence B is not translated in German in either MT system.


In this paper, we prepare negative words related to trouble information about a target product, such as "bad", "wrong" and "failure", as a negative word set.

imperfective forms The target tweets in this paper are written in Japanese.


We introduce three characteristics and a scoring method to the bootstrapping.

for the TS extraction process, we judge the presence of TEs in each sentence.


trouble information is a fraction of a percent of all tweets on Twitter.


We acquire only TEs with high confidence values as new TEs.

combined with the difficulty of the concrete definition of non-trouble tweets, collecting non-trouble tweets with high coverage is also a difficult task.


In our research, we use the words in tweets to calculate the speech components (as mentioned in §2.2 Step 5) for each user, and these speech components can be used for inferring Societas personal values with TwitterSocietas Model.

input: speech keywords KW for value component j, word set {W C} for all tweets, and the binary set V j of value component j.


As shown in Table 5, Weibo users tend to have the value "Curiosity" than Japanese Twitter users.

furthermore, we proposed a dynamic way to update the Twit-terSocietas Model automatically based on Twitter data.


5 Related Work The earlier work by (Zamal et al., 2012) proposed an approach of Twitter users' latent attributes inference including gender, age, and political affiliation with Twitter.

the wording on Twitter changes frequently, and the keywords used for inference in this model may be out of date.


4 Moreover, Naive bayes classifier was employed as an alternative choice for classifying Twitter data.

a data mining approach like microblog analysis, which is considered to have a sampling bias problem, as checked by (Mislove et al., 2011), can get objective "answers" for the "questions" without subjective biases.


A new value v new of the feature come to be obtained by multiplying the weight: Chen's method uses a correlation coefficient to define the weight.

in a classification problem, let (1) We can solve the classification problem by estimating the probability P (c|x).


Test data is also unlabeled data, but the former is smaller than the latter.

although the class distribution of labeled training data is uniform in each domain, Class distribution of the test data which can fit the problem of reality was set to be different in each domain.


The weight Chen defined can be regarded that measured the similarity of the label distribution P s of feature f in source domain and label distribution P t of feature f in target domain.

here, according to the similarity between the label distribution of the feature on source domain and the estimated label distribution of the feature on target domain, we set the weight on the features to reconstruct the training data.


In this experiment, the amount of unlabeled data is 1.5 times of the amount of test data.

when the difference between the domains is small, it is realistic that the problem of domain adaption is simply regarded as data sparseness problem.


In general, the supervised learning is used to create a classifier which is usually using a learning algorithm such as support vector machine (SVM) by labeled training data, then it is possible to identify the label of the test data using this classifier.

as a result, we define the new value v new of the feature as follows: if v new is a negative number after minus 1, v new = 0.


2012  termining the similarity of two words.

intelligence officials in Washington warned lawmakers a week ago to expect a terrorist attack in Saudi Arabia, it was reported today.


(2012) is based on the integration of eight metrics (TER, TERp, BADGER, SEPIA, BLEU, NIST, METEOR, and MAXSIM).

the translation edit rate (tER) metric (Snover et al., 2006) supports standard operators, including shift, substitution, deletion, and insertion.


It contains 5801 sentences pairs including 4076 for training and the remaining 1705 for testing.


Machine learning with unbalanced data usually leads to generation of a wrong classifier.

<m p>The music is incredibly powerful sound!</> Positive (p) about the aspect "Music (m)" <s n>It lacks a feeling of accomplishment after finishing.</> Negative (n) about the aspect "Satisfaction (s)" <g,s p,p>Since the graphics was beautiful, we got the satisfaction from just watching them.</> Combined tags are acceptable: Positive (p) about the aspects "Graphics (g)" and "Satisfaction (s)" The vector value of a word is computed as follows: where num ij and sent(asp i ) denote the frequency of a word w j in an aspect asp i and the number of sentences belonging to an aspect asp i , respectively.


Applying multi-label learning such as (Zhang and Zhou, 2007) to the task is one of the most interesting approaches although we used a binary classifier based on SVMs.

all sentences in a review do not always contribute to the prediction of a specific aspect in the review.


appear together in case of French and Italian restaurants signaling, perhaps, a long wait to get seated at such restaurants.

these aspect seed words are chosen manually which are, again, domain-specific.


Saurí (2008) developed a rule-based method to recognize the factuality of events, whose negation recognition can be regarded as a subtask.

saurí and Pustejovsky (2007) defined three markers: polarity particles such as "not" or "no," modal particles such as "may" or "likely," and situation selecting predicates such as "prevent" or "suggest."


The comparisons between the "ML" and "ML+all" and "Marneffe12" and "ML+all" suggest that n-gram clusters successfully generalize complex negations forms by their cluster IDs.

it seems quite difficult to write rules that cover the complex negation forms exemplified above.


"Sentiment Analysis" (Pang and Lee, 2008) has been researched on various corpus for years, such as product reviews (Wang et al., 2010), movie reviews (Whitelaw et al., 2005).

sina Weibo is a Chinese leading social network akin to Twitter.


Social media websites, such as Twitter and Facebook, have generated a great amount of public opinions on a variety of issues, especially hot events and emergencies.

we apply the best C2 model to predict the polarity for each tweet in Corpus.


In order to make sure whether there is a relationship between the real mood curve and the stock index curve, we annotated another larger dataset (denoted as Sample).

public mood on social events always goes to extremes.


In this talk, I will describe my forays in the analysis and processing of text corpora largely written in the Filipino language.

this fact is proof that the socio-political landscape of the times shapes the language of its people.


Acknowledging that language plays a vital role in the formation of a national identity, and hence, should be cultivated towards intellectualization, I propose that ICT could effectively be used to monitor language usage and provide added insights for language planners, in understanding the interplay between language and socio-political developments.

it has shown rapid and significant changes in its vocabulary, orthography and grammar, thanks to the Philippines' rich colonial history and the conscious efforts in the national and institutional levels to standardize the grammar and orthography of the language.


As a measure of the working memory capacity, the Japanese version of the reading span test was conducted (Osaka and Osaka, 1994).

moreover, identifying if readers can resolve a bridging reference with their own knowledge is important for user-oriented information extraction and document summarization.


The TOTAL is the total duration that the gaze spends within the area of interest.

this subsection presents information structure annotation.


Whereas the definiteness affected only TOTAL of the eye-tracking data, the specificity affected SELF, FPT, RPT, and TOTAL.

the animacy is a category about whether referents are alive.


We investigated the reading time (logtime) of NPs that were annotated with the information structure labels.

this allowed more natural reading because each participant could freely return and reread earlier parts of the text on the same screen participants were not allowed to return to previous screens.


(26) a. before INT(ne(ϕ))↓: B c S B A ϕ ∧ ¬B c S ϕ b. after INT(ne(ϕ))↓: P B c S B A ϕ.

the effects of no, yo, and ne on CCPs of FIs and, as a consequence, speech act felicity conditions are shown below.


1179 and Longman Spoken and Written English Corpus (Biber et al., 1999, pp.

bensal (2012) noted that active voice is more preferred than the passive voice, for it allows the speaker to express himself/herself in a more direct and emphatic manner.


The motivation of such a study is both to find an effective model of stylometric study without annotation and processing, as well as to test the effectiveness of the linked data approach to stylometric studies.

the tone motifs and word length motifs are both lexical feature that can be linked from other lexical resources and do not required annotated texts.


Both of these parsers are language-independent, which allows any language to be used in the parser without any compromise in accuracy.

this research used 100 Indonesian sentences from IDENtIC (Larasati, 2012) as the treebank.


In the third scenario, we compared the performances of ensemble parsers that use different algorithm combination.

voting system with unweighted scheme has a little higher accuracy than others (0.01%), because the resulting graphs are not reparsed, which make the individual dependency accuracy better than those that use reparsing algorithm.


thought 'Ken thought that Naomi was a fool.'

it is interesting that kare-ga 'he-NOM' co-occurs with NP-no koto-o.


Interestingly, (30b) licenses RTO as shown in (31).

we can give the feature specification of the sentence in (31) as (32).


For example, let A = ⟨a, b⟩ Returning to the word order of (10a), the following feature structure (14a) and (14b) can be applied.

it is licensed in (4b) with futot-teiru 'being fattened', though the predicate is neither the adjectives or nominal + copula da form.


Due to our method is initial step of NLP task, in this experiment we use translation accuracy of building SMT system as evaluation of our method.

in our method, we take the following strategy: 1.


Moreover, (Pham and Le-Hong, 2017) used a combination of Bi-LSTM, CNN, and CRF that achieved the same performance with (Le-Hong, 2016).

these additional features consist of part-of-speech (POS) and chunk tags that are available in the dataset, and regular expression types that capture common organization and location names.


(1) Ken-ga kami-ga nagai K-NOM hair-NOM long 'Ken's hair is long.'

it must be worked out how displacement of nonleftmost ga-NPs in <NP 1 , NP 2 , …, NP n > (in the sense of (9)) is precluded.


Recently, some research also showed that treating the parse tree as latent variables (Loehlin, 1998) can benefit the BTG tree inference but for preordering (see Figure 2).

the BtG terminal rule (t : X → f /e) is used to translate the source phrase f into the target phrase e while the straight and inverted rules (S : X → [X 1 X 2 ] and I : X →< X 1 X 2 >) are used to concatenate two neighbouring phrases with a straight or inverted order as following: where • stands for concatenation between strings.


They manually examined these posts and obtained a list of 28 tags relating to eating disorder and anorexia.

the tags are rarely used and are overpowered by the tags found in Figure 4.4b that they are frequently using.


In this case, people who are lying rarely using that kind of words because at the time they are lying, they have to think carefully in order to make their lies to be as perfectly possible.

after that, we translate the transcription using automatic machine translation for Indonesian-English.


We may also regard the "newly" discovered [tʃ] as an allophone of /ts h / in the Cantonese inventory, especially for the 20s generation.

as for the effect of vowel context, the substitution of /tʃ/ only occured after vowels of /ɔ/ and /u/ (p<.001), which are all back vowels (see Table 2).


For the control group, 100% sound were pronounced as /t h / as predicted, and we did not see any of the tokens with a palatalized sound change.

descriptive and pedagogical literature has shown the phonetic similarity of these alveolar and post-alveolar affricates [5]  (which is an underlining support to the clear-cut differences of these sounds), the real Cantonese speech by young generation suggests something different.


2006, Han and Storoshenko 2012, Kim 2013, as exemplified in (3).

like-Prs-Decl-Comp think-Prs-Decl 'Ii think Chelswuj likes me*i/himselfj.'


sohng (2004) argues that caki has inherent Φ-features with a third person.


Like the English will, in Korean and Mandarin Chinese, -(u)l kes-i and hui are used to express prediction.

from the corpus-based investigation, it is noticed that hui tends to entail a causal relationship, often indicating generality and habituality abundantly in the causal construction but also in the conditional construction, albeit fewer in number.


for simplicity and clarity, the scope of the investigation of this paper is limited to conditional and causal complex phrases, since -(ul) kes-i is often realized in single phrases as a continuity of causal or conditional statements, as in "Drinking two grams of cyanide causes death", which is approximately the same as saying "If somebody drinks two grams of cyanide, they will die" (Puente, et al.


(23) yinwei yidan huan ganbing, baiyanqiu Because-once-have-liver:disease, whites de bufen jiu hui chuxian huangdan Part-area-then-Mod-appear-jaundice 'Because once (you) get liver disease, the whites of the eyes will become yellow.'

in Mandarin Chinese, when expressing a causal conjunction with a causal connective yinwei, hui cannot have an epistemic meaning that expresses the speaker's epistemic assumption but still encodes a linkage between propositions in which q is contingent on p as in (13): (13) yinwei you ai， cai hui qidai because-exist-love, only:then-Mod-expect 'We expect because there is love.'


Crucially, the nominal bases involved are singular (or non-plural) forms, as in (14).

i remain agnostic about whether the information in the qualia structure is part of lexical knowledge or not.


I will argue in section 3 that they are stative participles in the sense of Embick (2003Embick ( , 2004.

22 The alternative with non-syllabic -ed poses no problems.


22 Specifically, on the assumption that syllabic -èd appears as a result of Root-determined contextual allomorphy, leggèd is predicted not to appear in denominal adjectives owing to the VI rule in (19)b.

second, we argue that the adjectivizing suffixed has no contextually determined allomorphs in denominal adjectives.


First, the -ed suffix of denominal adjectives behaves in the same way as that of adjectival and verbal passives in displaying phonologically conditioned allomorphy, as shown in (16).

i follow Arregi and Nevins's (2014) analysis of pluralia tantum nouns, where these nouns are assumed to have their n head specified for [−group], and, if Num is present in structure, they must appear with the Num head specified as [−singular].


unpredictable from their putative nominal bases.

the adjectives with syllabic -èd in 20 Marantz (2001).


Since the Major Subject (MS) regularly alternates with the Possessor of a sentence with a single Subject, it was natural to restrict the range of non-Subject GRs in that way.

this could be due to a couple of reasons.


So treating it as a guided principle is the maximal value / maximal expectation.

we find that 6.5% (304 sentences) of the sentences which contain bale and 5.2% (452 sentences) of the sentences which contain eryi cannot be used interchangeably.


Benveniste (1971) argues that language is the instrument of communication and taken over by the man who is speaking and within the condition of intersubjectivity.

chu (1986) and Liu (2000) believe that eryi expresses the mood of limitation.


Section 4 presents the data analysis and results.

people can use a lot of methods to express their mood and tone.


More specifically, while denotation represents the semantic meaning of the word, connotation often refers to the style and interpersonal emphasis of its usage in a specific context.

after the frequently used verbs were identified, the usage notes of dictionaries and thesarus demonstrating the fine differences of the verbs were employed in a two-part representation for lexical differentiation (DiMarco et al., 1992).


English and Italian source sensory domains in frequency-decreasing ordering (%), adapted from Strik Lievers 2015On the other hand, the frequency of target modes in Korean synesthetic transfers is similar to the finding of Strik .

2013, she found large-scale data results and more clearly presented that the so-called principle of directionality just reflects the "frequency" of synesthetic connection types, adding a few interesting interpretations about the motivation of English and Italian synesthetic mappings.


This author also believes that it could be the journalist's communicative strategy to accommodate a wider audience particularly the foreign ones who cannot decipher the meanings of local terms.

this paper demonstrates a trend of nativization of English in a rural area as seen in a local daily.


When asked about the benefits of using Facebook groups in the class, reasons why they liked it, and what challenges they encountered in using it, students reported a variety of responses, as shown in Table 4 below.

social media such as networking sites (sNss) are now part of the lifestyle of today's learners who are technosavvy and adept at maneuvering networked systems.


Parallel corpus is a valuable component needed in SMT to train models, optimize the model parameters, and test the translation quality.

since Japanese and Korean has the most similar characteristics in grammar structures (Kim and Dalrymple, 2013), these additional techniques will also be explored as additional processes.


For ID-KR translation, the dictionary translation help to translate the untranslated verb, such as "tidak yakin" as "아니다 확신하는", this translation is incorrect as a phrase.

it has been reported that direct MT model gives better performance compared to pivot MT model (Costajussa et al., 2013).


Tokenization for Indonesian corpus is based on spaces with the addition of tokenization to a word containing prefix ("ku-" and "kau-") and containing suffix ("-ku", "-mu" and "nya").

the translation process is employed by using n-gram matching (from 3-gram to 1-gram).


pianpianneng 偏 偏能，pianpianmeiyou 偏偏没有，pianpianxian 偏偏先，pianpianhen 偏偏有些.

if the subject is sent by a bidding team to represent them at the important final interview (instead of other team members).


In terms of filler-gap dependencies, there exists a gap position, which is the argument of an embedded verb, and an antecedent (or filler), which indicates the sentenceinitial wh-phrase in (1).

this indicates that the speaker obeys the wh-LF-movement to ban the embedded wh-word to have a matrix scope.


Following Saito (1989), the scope for wh-words is the entire sentence in nonisland sentences.

although her study proved the existence of wh-island, the preference to yes/no-reading would not be accepted as reliable if participants considered the tested sentences as unacceptable.


We also develop an annotation system that cooperates with a crowdsourcing service.

this approach is extremely work intensive.


NLP researchers have built corpora for various NLP tasks through crowdsourcing.

our ultimate goal is acquisition of real-world causal knowledge by exploting Wikipedia as an encyclopedia.


Methodologies used in researches concerning automatic document categorization are unique from language to language, depending on the structure and morphological rules of the specific language.

a 10-fold cross validation scheme was used to validate the performance of the multinomial SVM classifier.


Based on Table 2, the classifier was able to yield relatively high F-Scores, except that of Terrorism which yielded an F-Score of only 78.78%.

feature selection is language-dependent.


The separation frequency of Mainland 把关 baguan (45.74%) is significantly higher than that of Taiwan counterpart (1.19%), with a likelihood ratio of 38.437, indicating that 把关 baguan is about 38 times more likely to be used separately in Mainland than in Taiwan.

the results prove that empirically compared to separable VO compounds, inseparable ones are more likely to be used in a transitive way.


separation usages can only be detected in Mainland corpus).

if a VO sequence is less lexicalized, its probability of taking an object is higher.


For the middle layer, we use Long Short-Term Memory (LSTM) for each model of biRNN with 200 hidden states, and FFNN with a unit size of 200 and 100 from the near side of the input layer.

by using these approaches, word segmentation is not necessary, and the vocabulary to be handled is reduced; however, there are few studies that use the attention mechanism in character-based approaches.


The score for the t-th character score t is calculated as follows: By using score t , we can calculate the weight W t and MeanVector attention a m in a similar way to that in section 2.2.1.

negative samples were randomly sampled, so some positive samples are included in the data.


overall, our method (MeanVector attention with multitask learning) achieved an F-measure of 0.627 in F-measure, which is 0.037 higher than baseline method.


Assuming the words "delay" and "train" are included in the keywords, the tweet "xxx line is delayed by accident," which can be used as a news source, can be extracted.

these systems analyze tweets as information sources and extract useful information to assess the damage caused by large-scale disasters.


However, extracting useful information for news writers from the vast amount of social media information is laborious.

it has been reported that by using multi-task learning, the model can be generic and accurate (Luong et al., 2015b;Søgaard et al., 2016).


Our method analyzes each character in a tweet by using a Recurrent Neural Network (RNN) and then decides whether the tweet includes important information.

our method is character-based approach, not a word-based one.


Then, by using Word2Vec (Mikolov et al., 2013), each unit is converted into a 200-dimensional distributed representation.

for example, the method learned tweet including phrases related to fire like a "対岸 の火事 (the fire on the other side)" as a negative example.


When the features were added, the positive and negative criteria were clarified.

a lot of effort is required to find valuable information from among the large number of tweets sent every day.


In characteristic phrases, we exclude titles that contained common verbs or adjectives such as "生 きる (live)" and single-character titles such as "江 (Gou)."

when largescale incidents or accidents occur, secondary tweets such as retweets often occur, so the absolute number of tweets judged to be positive samples increases.


Enlarging the training data (increasing from 130k to 456k parallel sentences) improved both SMT and NMT models.

for neural machine translation, one of the basis frameworks is the encoder-decoder (Cho et al., 2014;Sutskever et al., 2014).


all verbs and adjectives in the corpus are separated into the stem and the desinence.


We show an example of KyWSD execution in Figure 2.

if the tag is the part of speech, KyTea learns a general morphological analysis model.


This problem has been ignored in conventional Japanese WSD.

a sense of the word not appearing in the training data is assigned by the dictionary.


Moreover, as explained above, ignoring senses not in the sense list provided by that task, there are 6,986 correct senses for 8,953 answered instances.

in this paper, we introduced the Japanese all-words WSD system called KyWSD, which we produced and launched.


kyWSD works under the operating system supported by kyTea, Linux, Windows, and Mac OS.


Second, tones can distinguish singulars from plurals grammatically (See Table 3).

my current study tried to answer three research questions, namely (1) how many surface contrastive tones does Twic East Dinka have; (2) What functions do tones have in phonology, morphology, syntax or semantics and (3) What are the contexts of tone sandhi in Twic East Dinka?


Fifth, a suffix [ɛ] with two kinds of tones indicates whether objects are visible and can be pointed at (i.e., deixis, distance information) (see (81)-(84)).

this tone sandhi happens only when both N1 and N2 are singular.


One disadvantage of chunk-wise translation is it cannot capture the con-text beyond each chunk's boundary.

this approach utilizes dialect embeddings, namely vector representations of Japanese dialects, to inform the model of the input dialect.


As we saw in the previous section, the dialects in geographically close regions are generally more similar to each other than those in other regions.

the use of similar dialects has been found to be helpful in learning translation models for particular dialects.


Regarding the dialect label order used for the input, our preliminary experiments indicated that the best models were obtained using input sequence (d) ( Table 1) for dialect-to-standard translation and input sequence (c) for standard-to-dialect translation.

the multi-dialect model demonstrated drastically improved the translation performance.


If majority of the models predict that the tag is different from the given tag of that word, that particular tag can be considered erroneous.

there is a need to build a model that reduces human effort.


The relative clauses (MSa) tend to require a shorter reading time than the appositional clauses (MSb) in TOTAL.

unlike self-paced reading, during eyetracking, all segments were shown simultaneously.


This paper presents a contrastive analysis between reading time and clause boundary categories in the Japanese language.


Figure 1 illustrates how the word representations of soft cheese, soft drink, and soft iron change from the initial representation of the word soft as a starting point.

in the example shown in Figure 1, since there are cheese, drink and iron as context-words of the target word soft, our approach generates word representations for each pair such as soft cheese, soft drink, and soft iron.


Moreover, the dimension was reduced to 200.

the use of the connected data of the original data and the encoded data is a feature-based method.


The simplest way to calculate the ratio is directly estimate P S (x) and P T (x), but in the case of complex models, the problem will be more complicated.

instance-based methods have not been studied as much as feature-based methods.


The problem of entailment is considered a problem of classification with two classes, a class "YES" and a class "NO."

the system utilizes techniques from Information Retrieval and Natural Language Processing to process a collection of Arabic text documents as its primary source of knowledge.


In this paper, we propose to construct a semantic and logical representation of Arabic texts (the question and the passages of texts).

we have obtained an accuracy of 74%, which is very encouraging compared to the size of the tag set used till now.


The content criterion assesses the generated online persona and the context of the story.

the thoughts element contains the user-generated content in a post's "What's on your mind?"


The story generator selects relevant assertions to form the persona description.

we decided to rely on the F1 score computed on macro-average (Van Asch, 2013) to utilize both precision and recall since F1 score provides the harmonic average between the two mentioned evaluation metrics: Computing the F1 score based on macro-average instead of micro-average (traditional computation) gives equal weight to the classes.


Among the four registers, fiction contains the highest proportion of predicative adjectives where descriptive use of a state of mind or emotion is common (e.g., afraid, aware, glad, happy).

the corpus results are summarized in table 4.


Large corpora are bound to contain noise in one way or another, which may arise from a complete mismatch between the source and the target sentence, an incompatible alignment at the sentence level, or at other times simply very poor translation.

the first translation for each of the example source phrases obviously demonstrates a more contextually dependent rendition.


Our results show that increasing rate of category sharpness differs between musicians and non-musicians.

lastly, duration asserts a stronger effect on between-and within-category discrimination patterns among tonal listeners.


For English musicians, a regression model with an extra quadratic term turned out to be significantly different than the model with only the slope and intercept terms, as suggested by a likelihood ratio test (χ2(1) = 8.75, p = 0.003).

(2014), our results indicate that musical training can in fact promote pitch processing and categorical perception in tone languages.


From the formulae, category boundary sharpness for both English musicians and non-musicians increased as stimulus duration increased, but English musicians showed a steeper slope, indicating a faster increment of sharpness of category boundary with increased duration.

the significant effects of pitch direction were found for most duration values, but only among pairs involving the vowel [i] (FEMI vs. REMI and FENI vs. RENI).


As for minimal duration required to produce and perceive pitch direction, our results showed that the minimum time required to perceive pitch perception was usually shorter than what is needed to produce pitch direction, similar to the findings reported for Chinese and English listeners (Chen et al., 2017), lending further support to the claim that physical constraints affect speech production than perceptual constraints do on speech perception (Janse, 2003).

although category boundary sharpness increased with duration among both English musicians and non-musicians, English musicians showed a faster increment than nonmusicians, indicating that musical experience draws greater benefits from extra stimulus duration.


The study thus hypothesized that if the increase in pitch range and level was caused by hyper-articulation, the speech rate should have been slow down simultaneously.

the tonal contrast t4 and t6 showed the most evident process of differentiation over time, starting with a merging state and ending up with clear separation.


BLEU is the most well-known automatic evaluation technology in assessing the performance of machine translation systems.

this shows that the automatic evaluation by linguistic test points is similar to the automatic translation metrics.


Kalyuga (2005) has proposed several types of structure for Russian emotion verbs as a whole.

first, the large majority of the hàipà instances comprise a nominative experiencer and an accusative stimulus (I) The stimulus can come before the verb by the use of the accusative marker duì/duìyú (II).


We applied the similar approach to tag the TSS to enhance the performance of scientific RC.

we execute the problem setting in computational linguistic domain, but we believe that this setting can provide useful guide to other domains, such as RC in biomedical domain.


We hypothesize that TSS can be utilized to improve the performance of scientific RC.

the entity X tends to be a research activity, such as "analysis", "survey" and "discussion" etc.


Questions in these systems are queried in a single question format, such that there is only one question per utterance.

understanding each part of the text written or spoken by the user is essential to QA systems.


One such instance from Ubuntu dialogue corpus is: why would you recommened archlinux ?

most of these systems suffer in question-answering accuracy, especially when speakers embed multiple questions within the same utterance.


Further, SDS can be performed in two ways, abstractive and extractive where the former method is aimed at producing denser summaries which appear to be written by a human while the latter picks out key sentences, phrases and words from the original document and stitches them together to form a coherent summary.

the word embeddings used are pretrained and out-of-vocabulary words are replaced by "unknown" token while computing a sentence vector.


• β: the most specific concept belonging to B(D, T, I), also called the bottom element.

approaches belonging to the CLR family are based essentially on the idea of considering the query as a new entry for the formal context.


The relation between a document and the information that presents it is a binary relation (the information presents the document or not).

this set of docu-1 http://sourceforge.net/projects/conexp/ Figure 3: there are a one concept contains in its intent the query terms (surrounded by a green circle) ments (noted R d ) to do this, we look for documents that satisfy to the query Q = t 5 ∧ t 6 ∨ t 2 .


There are several approaches for information retrieval based on concept lattice, we cite: information retrieval systems for medical documentation (Cole and Eklund, 1996;Cole and Eklund, 1999), software documentation (Linding, 1995;Priss, 2000) and Bioinformatic Databases (Smal-Tabbone et al., 2005).

it separates the conjunction operators from those of disjunction or negation.


then we needed to identify whether it expresses emotion(s).


as for the progressive aspect, both French and English generally mark it lexically (Li and Shirai, 2000;ayoun and Salaberry, 2008), although this can be done in a number of ways.


Bayona (2009) also notes that the factors that most facilitate L3 learning are: typological similarity to previously acquired languages (L1 or L2), proficiency in the L2, and recency (how recently the L2 has been activated).

the result that some learners transferred more from their L1 and more from their L2 is congruent with L3 acquisition studies such as Chin (2009) and Jin (2009) that suggest that L3 learners will transfer from either their L2 or L1, depending on proficiency in the language, recency, and typological similarity.


However, other studies contest that the evidence for the CPH is not as exact as thought and suggest that, for example, the number of years that one studies an L2 is more influential on final acquisition (Strid, 2017;Birdsong and Molis, 2001;Marinova-Todd, 2003;etc.).

the CPH is a controversial theory in SLA, with many researchers claiming that earlier exposure to an L2 (i.e.


Finally, our results are inconclusive as to whether onset age of an L2 or years spent studying the L2 had a stronger overall impact on learners (i.e.

the perfective aspect is marked in the same way in French and English, but differently in Burkinabe languages, but the progressive aspect is more similar between Burkinabe languages and English for present progressive marking.


An alternative explanation could therefore be related to how focus marking interacts with pre-existing prosodic boundaries, or else the tendency for boundaries to be strengthened at specific locations as a result of focus Finally, we found that the classifier did not pattern with respect to focus in the same way across the three acoustic measures.

fixed factors included only fOCUS condition.


The plot for T3 also suggests that third tone sandhi applied between the numeral and classifier, in that there is a dramatic lowering toward the end of noun, but not between the numeral and classifier.

its duration was not affected by focus condition, but it showed a higher mean F0 and greater intensity in the Num-Focus and NP-Focus conditions as compared to Noun-Focus.


Since many recent approaches to computational metaphor processing have used context-based features as input to the classification task (Shutova et al., 2012;Jang et al., 2015;Jang et al., 2016), the degree of success will largely be influenced by which part of the above life cycle the metaphor is in.

for the bLSTM, the input layer of the network consisted of 89 time steps, being the length of the longest sentence in the corpus.


Finally, the attention-based bLSTM with Word2Vec features proved to be the most effective out of all the classifiers, with features from the skip-gram algorithm providing the best results of an F-score of 84.61.

depending on the degree to which the metaphor is conventionalized in the language, it is expected to be far more difficult to detect using computational methods, since its domain essentially becomes indistinguishable from the rest of the context.


We regard it as important that a system communicates with its user via a language based on his/her personality to bridge the inconsistencies between the system's requirements and the user's attention and actions.

these blogs were written by 81 university students in the following four themes: sight-seeing in Kyoto, cellphones, sports or gourmet food.


The behavior and subjectivity tags are attached only within each DE range.

we regarded this extended self as self-behavior.


The coordinate compound is an indispensable part of Chinese.

(2) AB ≈ A + B The second one is AB ≈ A + B.


We observed almost the same average percentage of promises in both the winning and the losing speeches.

we manually transcribed each speech while listening to the speaker for best accuracy.


They were of special interest to the parties as well as to the people.

political discourses hold a great importance in the field of Critical Discourse Analysis.


Table between UniDic and WLSP (Kondo et al., 2018) developed an alignment table between UniDic and the WLSP 2 .

this example is assigned an article number for each SUW of (Nagoya), (tower), (Plaza), and (Hall).


The model generated from the dataset probably estimates approximately 0.75 as the trivia score of many instances.

we use the categories on wikipedia for this process.


As a criterion, we use nDCG@k (k = 5, 10).

they handled trivia   Score Maximum  A statue of Buddha with the Afro haircut exists.


sentences with high trivia scores for the purpose.


Table 4 shows the experimental result of the ranking task.

we need features for the machine learning methods.


The upper bound of the proposed method is shown in Table 3.

the update for the i-th parameter, θ t,i , at time step t, is defined as follows.


Generally, the proposed model tends to be robust for compounds of different character types (e.g., Famiポート (Fami Port) multimedia vending machine), whereas Neubig et al.

b 1 denotes a bias vector, and h t denotes the resulting hidden vector.


Table  5 shows a comparison of four examples for the current study and KyTea 0.4.6.

the proposed method correctly identifies the word.


Aligned Pairs: (Target-side Token, SPM Prediction) Verb Inflection (calls, called), (release, released), (win, won), (condemns, condemned), (rejects, rejected), (warns, warned) Paraphrasing to Shorter Form (rules, agreement), (ends, closed), (keep, continued), (sell, issue), (quake, earthquake), (eu, european) Others (tourists, people), (dead, killed), (dead, died), (administration, bush), (aircraft, planes), (militants, group)   Figure 7: The SPM aligns "welcomes" with "welcomed."

32nd Pacific Asia Conference on Language, Information and Computation Hong Kong, 1-3 December 2018 Copyright 2018 by the authors The SPM predicts the probability distribution over the source vocabulary q j at each time step j.


The attention distribution a t is calculated as in (Bahdanau et al., 2014): where v, W h , W s , and b a are learnable parameters.

because our model is based on their model, we describe their model in greater detail in this subsection.


These summaries are written by human editors.

the development and test pairs were extracted from the data of January 2016 to December 2016, which included 100 pairs of articles and summaries per month.


Then, in the case of the parallel type, the third sentence explains the first sentence; however, its content is different from that of the second sentence.

p gen is used as a soft switch to select a word from the vocabulary distribution P vocab or a word from the attention distribution a t .


First, we need to train structure-specific summarization models for the parallel and sequence types.

based on the above discussion, it is suggested that the first sentence should be correctly generated in order to evaluate the summary structure appropriately.


This, in effect, even counter-balances the differences in the normalised frequencies of 嗰 go3 across the three corpora.

while face-to-face conversations, public discussions, and interpreted speeches can all be considered spontaneous, they differ in at least the following respects: interlocutor relationship, expected audience, speaker freedom, and cognitive processes, which may partially account for the observed differences in the use of demonstratives.


Fear is typically triggered when a person thinks that some bad things are going to happen.

the emotion keyword(s) of each instance is indicated as <emo id=0> X </emo>, with its pre-event and post-event being manually annotated as well.


We used the Adam optimizer to learn the weights of the network with a default learning rate of 0.001.

alignments using graphone bigrams are similar to parallel corpora alignments.


Their system performed with better accuracy in terms of phoneme error rate.

the letter 's' is aligned with a null phoneme '_' that is not pronounced.


Both of them fails to be a felicitous continuation of (8a).

but see discussion in Potts (2005) and 4 Koev (2017).


The subscripts u and m in the translation lines stand for 'unknown to the speaker' and 'mentioned to the speaker previously' 1 respectively.

c. # …daanhai ngo m-zi hai bingo but I not-know be who '…But I don't know who he is.'


(32) Semantics of m-zi and WH (first version) ⟦m-zii / WHi ⟧ g = g(i) ∈ Dcf (33) A special compositional rule for EIs and RIs ⟦m-zii / WHi XP⟧ = ⟦m-zii / WHi ⟧ (⟦XP⟧ F ) For RIs, we suggest that the phonetic features of WH is acquired during derivation.


For the implementation of a GLM model, an initial model was constructed first.

to that end, we used a collection of multi-factorial analysis methods to compare native scholars' L1 corpora, respectively with two varieties of non-Anglophone scholars' nontranslated L2 corpora (L1 English vs. Quasi-L2 English vs. L2 English).


3 It was also widely accepted that translated versions may 'under-represent' linguistic features of their counterparts which lack "obvious equivalents" in original texts (Mauranen, 2007).

the CIs of the three sub-corpora groups did not overlap as well, which means the three groups can be separable according to the different behaviors of each sub-corpus.


In other words, the first syllable of each disyllabic word was rated on a 101point scale, which evaluated the degree of application of tone sandhi as well as the naturalness of tone production.

participants were presented with characters or phonetic symbols on the screen when hearing and pronouncing the words.


Consistent with native speakers, as Beijing speakers obtained 92.23 for real words and 91.42 for wug words with significant difference (p < .001), Cantonese speakers of TG and CG both significantly differed in producing real words and wug words.

the same sets of stimuli were used in both preand post-training recording sessions.


In current study, L1 Cantonese speakers were invited to participate in pre-and post-training recording sessions.

odd trials were naturally produced sandhi stimuli and even trials were the synthesized stimuli without tone sandhi.


Until now, most work on error correction using NMT model aimed at correction for English text.

for example, Web search engines such as Google and Bing typically perform spelling check on queries, in order to retrieve documents better meeting the user's information need.


The rating score increased (towards 2.5 or 3) as the duration lengthened.

the predictions for the production study were that a) t3S syllables with low vowels should be produced more t3-like, b) t3S syllables with longer duration should be produced more t3-like, and c) a null hypothesis was assumed for syllables with different rimes.


ProsodyPro generated the intrinsic duration of each syllables and turned all the syllable durations into a normalized time.

duanmu (2007) maintained the view that all Mandarin stressed syllables (i.e., syllables carrying lexical tones) occupy two rime slots, that is, although a simple rime, V in a stressed CV is counted as occupying two rime slots, and in this view, the length of V in a stressed CV syllable is considered the same as the length of VG and VN in CVG and CVN syllables.


This result proves that the information in the exposition is vital for choosing a correct option.

climax: She exited the airport and was struck by the heat.


To discuss how these matching features influence the model, we design a series of experiments and give further analysis on the learning curves of the test set.

this lacks an overall representation about the distilled exposition itself.


where the Japanese functional expression is in bold will be expected to be corrected as "行きましょう。", because the correct usage of Japanese verb conjugation rules in this phrase depends on the Japa-nese functional expression "ましょう (Let's)".

・BCCWJ 4 : The Balanced Corpus of Contemporary Written Japanese (BCCWJ) is a corpus created for comprehending the breadth of contemporary written Japanese.


・Lang-8 Learner Corpora: this is a largescale error-annotated learner corpora, covering 80 languages.

we proposed a character-based neural sequenceto-sequence model for the task of correcting grammatical errors on Japanese functional expressions.


This paper studies Heavy NP Shift (HNPS) from the perspective of parsing using Minimalist Grammar.

in the example, the parser starts building the derivation tree from a CP (step 1-2); "un-"merges the CP into C and T P with an EPP movement landing site (step 2-5).


Given the processing predictions, complexity metrics favor rightward movement analysis over the rest.

since structural properties of a sentence predicts how hard it is for humans to process it, it is unclear what processing predictions these analyses make, nor is it clear whether these predictions are born out in observed human processing preferences.


In the phonological system of Hong Kong Cantonese, there are seven long vowels /a, i, u, y, ɛ, ɔ, oe/ (Shi et al., 2015).

flege and Liu (2001) also revealed the important roles that motivation and L2 input played beyond the critical period impact in the process of nonnative language learning.


Character and subject intercept as well as subject slope for vowel type were included as random effects.

here arise the two questions: Why was significance only revealed for AOA but not for AOL?


Regarding the relationship of accent ratings and learning factors, the amount of Cantonese use is proven to be the most determinant indictor for learners' perceived accent, followed by AOA, LOR and Urdu use.

the accent rating result for the new vowel /ae/ did not clearly support the model, and the acoustic results for new vowel demonstrated that the experienced learners could articulate /ae/ in the same way as English natives did, unlike the inexperienced learners.


Table 1 presents the global polarity distribution for each language in the MDSU corpus.

in the future, we plan to attempt non-linear transformation methods and more task-oriented deep networks.


This is also the reason why the most typically used methods of MSA have been based on the above-mentioned MT.

table 2 shows the cosine distance decrease situation in the test sets for the two kinds of transformation methods.


(2013) proved the effectiveness of employing gender information, but their classifiers are not designed for multilingual settings.

they created separate models for each language, whereas we developed a single parametersharing model for all languages.


This study calculated the average consistency (AveCon) for all the 406 Chinese character (CC) families.

average consistency is also strongly affected by each family's powerful syllable and its K-C correspondent rate (r = 0.980, p < 0.001).


Adequency 4 The meanings of the two sentences are the same.

higher marks indicate better output) based on the criteria shown in Table 3.


In Figure 1, the complex word " (rich)" is substituted by " (much)".

"LexSub" obtains only three candidates at the maximum for one complex word from the paraphrasing dictionary described in 4.1.


In Japanese, substituting words surrounding a complex word together with the complex word is sometimes necessary.

this model predicts the previous token t k considering the future sequence (t k+1 , ..., t N ).


(2015) proposed a model called distillation and were able to train a model which was more compact than the original one.

first, this model takes two sequences: words and POS tags.


In this paper, we trained the system on a training set containing word problems with single operations and showed that memory network based architecture was able to learn to generate such equations.

system could not identify the direction of transfer for verb 'borrow' which resulted in an erroneous prediction of order of equation components.


GOCE applies the appropriate content extraction algorithm based on the classified genre of the page.

otherwise, we extract the whole text of the parent node.


Our evaluation showed that the coherence features result in higher accuracy than that of state-of-theart methods on different granularity of German text.

computer-translated text detection task has been interested by numerous researchers.


The scarcity of large corpora in reading disambiguated words is a major limitation in linguistic analysis and the initiation of a statistical approach to word reading disambiguation.

the extreme right column of table 3 shows the adoption rates of the sentences obtained by the simulated conventional dataset construction procedure with BCCWJ, and the average of the adoption rates was calculated.


At the moment, it is considered that easier tasks might be appropriate for the use of crowdsourcing than writing pronunciation tagged sentences.

although longer expressions such as " (person who is cooking)" and " (people who have knowledge)" mean the same as the shorter expressions of " " and " " , they may not be as commonly found in natural documents as compared to the shorter expressions.


Homographs are words that share the same written form as other words but have a different meaning, and can be classified into either homonyms or heteronyms, depending on their pronunciation, e.g., homonyms have the same pronunciation, such as lie (untruth) [lÁi] and lie (to recline) [lÁi], whereas heteronyms have different pronunciation, such as desert (region) [déz@rt] and desert (to leave) [diz'@:rt].

statistical tests showed that the difference in the average correct rate was statistically significant (p<0.01).


The corpora are used to construct models for disambiguation and the disambiguation accuracy is strongly affected by the size of the corpora.

four sets were used as training data and the remaining set was used as test data for 5-fold cross validation.


In the WordNet, each word belongs to a synonym set, "synset," which includes several synonyms.

limits are anticipated for the number and varieties of sentences that one person can write.


We extracted 82,892 instances whose format is the same as that in Figure 3.

(1) Bag-of-Words (BOW) for morphemes in an argument and its head verb.


The instances of GDA were divided into development (85%), training (5%), and test (10%) data.

this is because large-scale corpora annotated with these three labels have been developed (Kyoto Corpus (Kawahara et al., 2002) and NAISt text Corpus (Iida et al., 2007)) and widely used 1 .


Because of the flexibility of the neural-network structures, transfer learning can be easily implemented by changing the network structure.

we used simple neuralnetwork architectures to focus on clarifying what input features are effective, which learning models are powerful, and how different labeled corpora can be effective for the target label set.


Each subtask has three datasets: train, dev, and test.

we used the GloVe model of 300 dimensions.


For the classification subtasks EI-oc and V-oc, we use the additional metric Pearson correlation calculated only for some emotion like low emotion, moderate emotion, or high emotion.

each expert, in itself, can be a separate Regression/Classification model like Multi-level Perceptron (MLP) model or Long Short-Term Memory (LSTM) model or any other model that best suits the data and task at hand.


Intuitively speaking, the TPS of a given dependency type in a given corpus indicates the average occurrence of that dependency type in a sentence in the same corpus.

the raw texts without tags (downloaded collectively as a data-only file from the website of ANC: http://www.anc.org/MASC/Download.html) were parsed through the Stanford Lexicalized Parser v.3.7.1 after some parts of the texts (titles, headers, dates, unconventional punctuations, etc.)


Finally, we evaluated the F1 score of different labels individually to identify which type of entity is more difficult for the model to identify.

final representation of a word is obtained by concatenating the left context − → h t and right context We use 150dimensional LSTM in forward and backward direction so that, a 300-dimensional vector representation is learned for each word.


If the word sequence is provided in the reverse direction as well to a CRF model, identifying that the word Medical is part of an entity type Organization (I-ORG) will help the model to realize that the ambiguous word Jones is also part of Organization entity (B-ORG).

weights c are the parameters to be learned.


Problem Statement: We are given a general purpose dependency parser PAR (e.g., Stanford Parser), a large-scale corpus CORP, and a contend word W. Our goal is to induce a set of grammar patterns, p , ..., p k , for W present in CORP using PAR.

learners can discover the patterns of a word from the use of language by themselves (cf.


Typical linguistic search engines such as COCA and COCT usually fashion a bottom-up approach by providing a wealth of examples for inductive learning.

(Hunston, 2000) for English pattern grammar) of a Chinese word, corresponding examples, and the frequency, helping CSL learners to use a word authentically in writing.


By simplifying PoS, we reduce the granularity of patterns and thus make the use of patterns easier to understand.

this approach is not optimal because it encourages a more bottom-up rather than top-down display of concordance lines and the users can only examine one example after another without a structure to follow, making discovery of patterns bottomup a slow and ineffective learning process.


Table 4 presents the numbers of Type 1 and Type 2 spoonerisms in development and testing sets.

we have also shown the effectiveness of using Vietnamese language model and dictionary for detecting spoonerism in Vietnamese sentences.


GREET refers to an animate object, usually a person, which is being greeted in a chat.

lSTM architecture is used as the main layer.


This syntactic information plays a pivotal role in solving SRL problem (Punyakanok et al., 2008) as it addresses SLR's long distance dependency.

semantic Role Labeling (sRL) has been extensively studied, mostly for understanding English formal language.


The attention mechanism firstly collects the context information by multiplying trainable weights with all the vectors from every time step of the last LSTM output.

by only using WE + POS as the features, combined with DBLSTM, the model can achieve compelling result.


Few studies have explored the oral production, which is a kind of instantaneous task where more attention is paid to semantics and pragmatics.

this section investigates the influence of English proficiency and production form on the frequency of use of the six types of tCC.


We found that L1-Chinese learners at intermediate level tend to use more MDCs, while no difference in the use of BGCs is found between the two level groups, and that the incidences of MDCs and BGCs are substantially higher in oral production than in written production.

a certain relation holds between these two parts.


The OC texts contain QA texts like dialogue.

table 6 shows examples analyzed correctly by the Vote model, but not by the All model.


When we decrease during training, will stay away from core words.

the most important message in the experiments is a suitable manual constraint will certainly help the network extract more effective, robust features and achieves a better score than traditional attention mechanism does.


Actually, features extracted by both CNN and RNN are, in some way, compatible and unique.

we observe that our model achieves new state-of-the-art result on this dataset.


Table 1 shows that the corpus in the domain "books" is significantly larger than the others.

in real applications, the source domain S in the learning stage may be different from the target domain T in the testing stage, In this case, the classifier learned in the source domain S is ineffective in the target domain T .


To illustrate, for the perceived-to-be-serious type, medical advice was always present together with medical diagnoses.

(in press), by coding levels of a variable as either 1 or -1, zero is between the two levels and represents the lack of difference.


We observed two notable trends in the results.

frequency Polarity   anxiety  2233  neg  meds  1229  neu  medication  934  pos  disorder  698  neg  psychiatrist  382  neu  adderall  320  pos  suicidal  316  neg  disability  145  neg  abusive  136  neg  insomnia 131 neg Table 3: A set of words that appear only in the high f2 weighted group compared to the low f2 weighted group and their polarities derived by SentiWordNet.


The overall architecture of Feature Attention Network is shown in Figure 1.

p) denotes a sequence of vectors, namely a matrix.


We focus on the order of words among other styles and use the distribution of part-of-speech tags.

to address this issue, we propose Feature Attention Network (FAN), inspired by the process of diagnosing depression by an expert who has background knowledge about depression.


In order to improve generalization, we used dropout and an L2 regularization.

our model uses smaller training data as input due to limited computing power, showing lower performance than the state-of-the-art model that uses three times more data than ours and is trained in a less interpretable way.


'Hana poured water over Taroo, but he didn't get splashes of water.'

[-ar-ta > -at-ta] Note that, when the verb in (8) is causativized and turned into a ditransitive, the ambiguity disappears and the newly added nominative argument and the "demoted" dative argument are interpreted as an agent and an (intended) recipient, respectively.


At the core of their analysis is the assumption that have introduces an argument but does not assign its own theta-role to that argument, whose interpretation is determined at LF (or at the C-I interface under current conceptions) based on have and its complement.

i assume that this conventional association is stored as part of our encyclopedic knowledge, which is invoked when a particular set of lexical items are combined to form a verbal predicate.


Hitherto, we have distinguished the sentence final particle k'ɯ from the verb k'ɯ.

1 It is worth mentioning that k'ɯ is free to sentences indicating different time of events, while qu is confined to sentences indicating the future events.


Adopting corpus analytical procedures, we identified two major must constructions, [must+be] and [must+"ve/have], whose central member [there+must+be+some] conducts the topic extending function while [she+must+"ve/have+been] is related to the speaker"s evaluation of the condition of an individual identified as she.

it is also found that when the construction appears at the beginning of an utterance, it is often preceded by markers like but, mm, well, er, yes, or yeah, which indicates the speaker"s readiness to launch a negative comment or counter argument.


By treating modal semantics as ambiguous, the monosemous notion provides a common ground for the interpretation of different senses expressed by the modal verbs.

section four presents the result, section five discusses, and section six concludes the study.


The rate of articulation does not reflect how much linguistic information, especially meaning as expressed by propositions, is conveyed or represented in a linguistic unit like a syllable.

more importantly, it is about "what" (meaning) is being communicated.


Nevertheless, the children showed significantly greater variance (0.0004) than the adults (0.0001) (one-tailed variance test: F(34,28) = 2.59, p < .01).

how communicative efficiency of a human language can be quantified is not a simple question.


If no such words were found in the sentence, a 0 score was applied.

the performance of VietSentiLex was evaluated by analyzing actual reviews from other datasets and domains.


The Harvard General Inquirer (2002) has 4208 words that are classified as positive, weak positive, neutral, weak negative, and negative.


Similarly and most famously, Halliday (1979;1985) indicated that speech and writing are both complex systems but in different ways: speech is more complex in terms of sentence structures while writing in terms of high lexical density.

it is an abstract machine that can be in exactly one of a finite number of states at any given time.


Only with the measurement of both lexical and structural variations can we better index language complexity.

the ellipses in Figure 3 means the state jumps out from the current status into a new status (i+1 or 0 to i) and a same process is iteratively conducted.


Ha Jin uses onceoccurring word types (60.2%) at a similar rate to that of the native speakers (61.0%), which is conspicuously higher than that of the advanced learners (51.6%).

as a point of reference, we obtained the chi-square value of a pair of novels by the native speakers -The Human Stain and Tinkers.


Wu ( , 2018a, Wu & Kuo (2012), and so on, examine different temporal modifiers and their syntactic/semantic behavior.

under the scenario given above, yuánlái2 involves reported evidence, e.g.


are considered involving epistemic modality.

in (4b), cāi 'guess' takes a stipulation or conjecture as its complement.


While Wu (2012a) and Wu & Kuo (2012a) are on the right track in terms of the temporal semantics for běnlái and yuánlái, there are two semantic properties of yuánlái which have yet to be explained.

a re-examination of yuánlái2 is called for.


In this scenario, the overall F1 score increased from 84.67 to 85.06 (see Table 3), which indicated that the external information from LM was helpful for the NER task.

while with the use of pre-trained language models, model parameters were not be updated during the iterative process of named entity recognition model.


it is a low-resource language, Mongolian NLP resources are very rare.


We evaluated the proposed models with a Japanese balanced corpus and confirmed the effectiveness of the candidate pruning by showing 0.056 point increase of accuracy.

(I NOM ) see v1 fashionable buildings ACC in the nearby shopping district DAT recently.


Sharing the signifiers clearly does not entail affinity for the linguistic status, but sharing the signified could mean sharing the (lexical) semantic system representation of conceptual systems.

the greater the extent to which the meaning conveyed by the character and its radical is shared, the more transparent is the character.